In one project, we are examining how particular sets of neurons are chosen by the brain to guide decisions. Whenever humans or animals see sensory stimuli, many brain areas are activated. We hypothesize that there are particular representations particular patterns that are created in each brain area, some of which are optimized for decoding and some of which are optimized for other kinds of information processing. We are training mice to report perception of sets of visual stimuli which have decodable representations in different cortical regions. This work will shed light on which areas the brain decodes for behavior, and why it chooses those areas for decoding. In a second project, to understand how neuronal activity patterns give rise to behavior, we are changing the activity of populations of neurons with one-photon stimulation, and also of single neurons with two-photon stimulation. This approach allows changes in neural activity patterns in mammals during behavior, and it opens the door to studying how animals' choices depend on patterns of neuronal activity. We have achieved stable psychophysical performance in mice in the laboratory, and collected data in which we use the instruments to evoke stimulation patterns. We hypothesize that the brain regards as similar, for behavioral decisions, many different patterns that share similar statistical structure. A third project is aimed at tracing the flow of information from one area to the next within the cerebral cortex to understand the circuits that underlie decoding. We are labeling both anatomically and functionally neurons that project among several visual cortical areas. By activating and inactivating these projections during behavior, we are measuring which projections are used in decision making.